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Identification of MicroRNA-Related Tumorigenesis Variants and Genes in the Cancer Genome Atlas (TCGA) Data
MicroRNAs (miRNAs) are a class of small non-coding RNA that can down-regulate their targets by selectively binding to the 3′ untranslated region (3′UTR) of most messenger RNAs (mRNAs) in the human genome. Single nucleotide variants (SNVs) located in miRNA target sites (MTS) can disrupt the binding o...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7565843/ https://www.ncbi.nlm.nih.gov/pubmed/32824926 http://dx.doi.org/10.3390/genes11090953 |
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author | Li, Chang Wu, Brian Han, Han Zhao, Jeff Bai, Yongsheng Liu, Xiaoming |
author_facet | Li, Chang Wu, Brian Han, Han Zhao, Jeff Bai, Yongsheng Liu, Xiaoming |
author_sort | Li, Chang |
collection | PubMed |
description | MicroRNAs (miRNAs) are a class of small non-coding RNA that can down-regulate their targets by selectively binding to the 3′ untranslated region (3′UTR) of most messenger RNAs (mRNAs) in the human genome. Single nucleotide variants (SNVs) located in miRNA target sites (MTS) can disrupt the binding of targeting miRNAs. Anti-correlated miRNA–mRNA pairs between normal and tumor tissues obtained from The Cancer Genome Atlas (TCGA) can reveal important information behind these SNVs on MTS and their associated oncogenesis. In this study, using previously identified anti-correlated miRNA–mRNA pairs in 15 TCGA cancer types and publicly available variant annotation databases, namely dbNSFP (database for nonsynonymous SNPs’ functional predictions) and dbMTS (database of miRNA target site SNVs), we identified multiple functional variants and their gene products that could be associated with various types of cancers. We found two genes from dbMTS and 33 from dbNSFP that passed our stringent filtering criteria (e.g., pathogenicity). Specifically, from dbMTS, we identified 23 candidate genes, two of which (BMPR1A and XIAP) were associated with diseases that increased the risk of cancer in patients. From dbNSFP, we identified 65 variants located in 33 genes that were likely pathogenic and had a potential causative relationship with cancer. This study provides a novel way of utilizing TCGA data and integrating multiple publicly available databases to explore cancer genomics. |
format | Online Article Text |
id | pubmed-7565843 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75658432020-10-26 Identification of MicroRNA-Related Tumorigenesis Variants and Genes in the Cancer Genome Atlas (TCGA) Data Li, Chang Wu, Brian Han, Han Zhao, Jeff Bai, Yongsheng Liu, Xiaoming Genes (Basel) Article MicroRNAs (miRNAs) are a class of small non-coding RNA that can down-regulate their targets by selectively binding to the 3′ untranslated region (3′UTR) of most messenger RNAs (mRNAs) in the human genome. Single nucleotide variants (SNVs) located in miRNA target sites (MTS) can disrupt the binding of targeting miRNAs. Anti-correlated miRNA–mRNA pairs between normal and tumor tissues obtained from The Cancer Genome Atlas (TCGA) can reveal important information behind these SNVs on MTS and their associated oncogenesis. In this study, using previously identified anti-correlated miRNA–mRNA pairs in 15 TCGA cancer types and publicly available variant annotation databases, namely dbNSFP (database for nonsynonymous SNPs’ functional predictions) and dbMTS (database of miRNA target site SNVs), we identified multiple functional variants and their gene products that could be associated with various types of cancers. We found two genes from dbMTS and 33 from dbNSFP that passed our stringent filtering criteria (e.g., pathogenicity). Specifically, from dbMTS, we identified 23 candidate genes, two of which (BMPR1A and XIAP) were associated with diseases that increased the risk of cancer in patients. From dbNSFP, we identified 65 variants located in 33 genes that were likely pathogenic and had a potential causative relationship with cancer. This study provides a novel way of utilizing TCGA data and integrating multiple publicly available databases to explore cancer genomics. MDPI 2020-08-19 /pmc/articles/PMC7565843/ /pubmed/32824926 http://dx.doi.org/10.3390/genes11090953 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Li, Chang Wu, Brian Han, Han Zhao, Jeff Bai, Yongsheng Liu, Xiaoming Identification of MicroRNA-Related Tumorigenesis Variants and Genes in the Cancer Genome Atlas (TCGA) Data |
title | Identification of MicroRNA-Related Tumorigenesis Variants and Genes in the Cancer Genome Atlas (TCGA) Data |
title_full | Identification of MicroRNA-Related Tumorigenesis Variants and Genes in the Cancer Genome Atlas (TCGA) Data |
title_fullStr | Identification of MicroRNA-Related Tumorigenesis Variants and Genes in the Cancer Genome Atlas (TCGA) Data |
title_full_unstemmed | Identification of MicroRNA-Related Tumorigenesis Variants and Genes in the Cancer Genome Atlas (TCGA) Data |
title_short | Identification of MicroRNA-Related Tumorigenesis Variants and Genes in the Cancer Genome Atlas (TCGA) Data |
title_sort | identification of microrna-related tumorigenesis variants and genes in the cancer genome atlas (tcga) data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7565843/ https://www.ncbi.nlm.nih.gov/pubmed/32824926 http://dx.doi.org/10.3390/genes11090953 |
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